Endocrinology

Menopause

Latest AI and machine learning research in menopause for healthcare professionals.

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An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning.

Insect monitoring methods are typically very time-consuming and involve substantial investment in sp...

Non-Rigid Respiratory Motion Estimation of Whole-Heart Coronary MR Images Using Unsupervised Deep Learning.

Non-rigid motion-corrected reconstruction has been proposed to account for the complex motion of the...

Deep Learning-based Recurrence Prediction in Patients with Non-muscle-invasive Bladder Cancer.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by frequent recurrence of th...

Combined effects of volume ratio and nitrate recycling ratio on nutrient removal, sludge characteristic and microbial evolution for DPR optimization.

The optimization of volume ratio (V/V/V) and nitrate recycling ratio (R) in a two-sludge denitrifyin...

An embedded system for the automated generation of labeled plant images to enable machine learning applications in agriculture.

A lack of sufficient training data, both in terms of variety and quantity, is often the bottleneck i...

Quantitative analysis of brain herniation from non-contrast CT images using deep learning.

BACKGROUND: Brain herniation is one of the fatal outcomes of increased intracranial pressure (ICP). ...

Non-destructive detection of blueberry skin pigments and intrinsic fruit qualities based on deep learning.

BACKGROUND: This paper proposes a novel method to improve accuracy and efficiency in detecting the q...

Deep-learning-based multi-class segmentation for automated, non-invasive routine assessment of human pluripotent stem cell culture status.

Human induced pluripotent stem cells (hiPSCs) are capable of differentiating into a variety of human...

The Utility of Artificial Neural Networks for the Non-Invasive Prediction of Metabolic Syndrome Based on Personal Characteristics.

This study investigated the diagnostic accuracy of using an artificial neural network (ANN) for the ...

Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning.

Portable X-ray fluorescence (pXRF) and Diffuse Reflectance Fourier Transformed Mid-Infrared (DRIFT-M...

Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation o...

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public healt...

Intensity non-uniformity correction in MR imaging using residual cycle generative adversarial network.

Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue typ...

Bone Mineral Density and Content Among Patients With Coronary Artery Disease: A Comparative Study.

INTRODUCTION: Some studies indicate an association between coronary artery disease (CAD) and osteopo...

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer.

We apply for the first-time interpretable deep learning methods simultaneously to the most common sk...

Impact of chronic intermittent hypoxia on the long non-coding RNA and mRNA expression profiles in myocardial infarction.

Chronic intermittent hypoxia (CIH) is the primary feature of obstructive sleep apnoea (OSA), a cruci...

Dose-dependent effects of ultrasound therapy on hepatocellular carcinoma.

Non-invasive ischemic cancer therapy requires reduced blood flow whereas drug delivery and radiation...

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